Monthly Archives: March 2016

Today, I was thinking about the power levels[1] of the various adversaries that the TNG[2] crew had encountered. They faced some truly powerful adversaries, like the judging trickster god Q, alongside challenges which were only challenging because they were being polite (anything to do with Lwaxana Troi or almost anything to do with the Ferengi), or because of the Prime Directive .

At the same time, they faced a number of challenges which of a relatively similar power level (Most things to do with the Klingons and Romulans), and more often than you think, the challenge was within them, or within Starfleet.

I defined ‘high-powered’ challenges as those where firing phasers would only make the problem worse, so the crew must needs turn to guile. ‘Equal-powered’ challenges are those situations where firing phasers would lead to a toss-up. ‘Low-powered’ challenges are those where phasers or transporters would solve the problem handily[3]. ‘Self-powered’ challenges are those where the conflict is inside the crew, or between crew members, or between all or part of the crew and Starfleet. So, without further ado:

Season 1 (25 episodes):
High: 10
Equal: 4
Low: 7
Self: 4

Season 1 starts with a Q episode, and of the first few seasons is the one with the most high powered adversaries. TNG also had not totally found its footing around the introspective episodes (the closest they came was the fanservice ‘Naked Now’ and Picard reliving his past on The Stargazer in ‘The Battle’), but was well on its way with a sheaf of episodes which only contained conflict because of the Prime Directive[4].

Season 2 (22 episodes):
High: 6
Equal: 4
Low: 6
Self: 6

A couple of good Klingon stories (K’Ehleyr!), we encounter the Borg for the first time, a couple of good Data stories. A workable season, reasonably even all around.

Season 3 (26 episodes):
High: 8
Equal: 3
Low: 8
Self: 7

A number of Prime Directive/Ethical stories, Riker getting himself into trouble, Tasha returns! And Tin Man(!), one of my favourites, if only for the poignant ending scene, where Tam finally finds his Gomtuu, and peace[5].

Stay tuned for the next update, where we learn that Data is actually a high-powered adversary.

Note Bit thanks to Jammer’s Reviews of TNG, which inspired and also made this a lot easier, with 3-line summaries of the episodes.

[1]Q is > 9000.

[2]Star Trek: The Next Generation.

[3]Although possibly with some casualties, in a hostage situation.

[4]Not necessarily a bad thing, just pointing it out.

[5]Also an excellent allegory to help understand people who are highly sensitive.

It was happening again. Every time he started strumming his guitar, his bass would start to walk, and his eyebrows would sneak away.

The bass walking made sense. It did that every day. Without it, he couldn’t Ska at all. But he never understood his eyebrows. They always came back a few hours later, seemingly contented and full of glitter.

The handle existed, as it always had. It had vague recollections of of being in a box (or was that bauxite?) at some point, but now it was a handle, handling hands which would otherwise have to handle some other handle.

Words were difficult sometimes, but that was okay. Few people spoke to it. But it did appreciate those few who did. Like those few who thanked the elevatrix when it brought them to the correct floor.

Now it was turning…from the other side? This was most unusual. Very rarely was it turned from its back side. This was shaping up to be a most unusual day.

Fruit and Ice Cream. One of my favourite things in the world. Where does it come from? As far back as I can remember, it’s been one of my favourite treats (especially bananas!). I think it comes from both sides of my family. I have very specific memories of combining Neopolitan[1] ice cream with bananas, I’m sure both with my Baba and Grandma.

S and I were walking down the street today, and were thinking about the Internet of Things. Now, it’s a buzzword, and should be taken with a similar-sized grain of salt to all other similar buzzwords.

So we attempted to come up with the worst ideas possible for an Internet of Things.

The first idea was to put chips/sensors in each block in the sidewalk. But thinking about it, that would be really useful. Similar to rail lines[1], there is a widely distributed infrastructure, and checking each part individually is expensive.

Then we thought of putting individual chips/sensors in each tile in a person’s house. How silly would that be? But then you could know exactly what the person was doing, turn lights on and off correctly, rather than the current primitive motion sensors, help people track a daily routine, all kinds of things.

But the last idea we came up with led to the title of this post. What if every cracker you ate had a sensor/chip in it? You would have an almost continuous stream of data about your digestive system, what you were eating, how your body was responding to it. Think of the advances in nutrition science!

“Any sufficiently complex computer system is indistinguishable from a biological system.” -Me

So, I like to joke that I find all computer languages equally difficult[1]. The interesting corollary to this is that this also seems to apply to complex systems in general. I approach a complex computer (or other) systems in the same way that I would approach a biological system:

1) Look at the visible behaviour/symptoms/phenotype of the system[2]
2) Assume that there are some number of internal processes in the system, each doing the job they ‘think’ is correct
3) Build a mental model which describes the visible behaviour
4) If debugging a problem, this should greatly narrow down where you investigate

Steps 2) and 3) above are where I think my school training (engineering and science) were the most useful. Our engineering program seemed to focus on the fundamentals and underlying systems, so that one would have a pretty good idea of what individual system components are capable of[3] (and some idea of what the system as a whole is capable of).

The systems I understood most intuitively[4] were chemical systems, probably because my dad and his dad were both chemical engineers. You have a huge number of molecules[5], each doing its own thing, and in aggregate, they exhibit complex behaviour. When you’re dealing with inorganic compounds, you can (most of the time), simulate them in bulk, but when you’re dealing with organic compounds, the complexity explodes and all kinds of strange boundary effects become important.

At this point, you need to switch abstraction levels, also something I remember from engineering, from the micro- level to a level of slightly or substantially more abstraction. At this point, having an intuition about biological systems becomes much more useful.

I’ll use an example to illustrate. At one point, a number of years ago, I and my team were trying to debug why throughput on a system seemed to be capped at a number below the theoretical maximum. Like any flow system, there must be a number of sequential steps that your data or fluid or what have you must flow through. After we built this mental model, it was a matter of looking at readouts and logs to find the graph that had an asymptotic curve showing at which step the system was maxing out. Then we had to fix it, but that’s another story.

[1]This is probably not strictly true. I remember finding Fortran 77 more difficult than usual, and Javascript mind-bendy.

[2]I use ‘behaviour/symptoms/phenotype’, because we might be debugging a problem, or we could just be trying to better understand the system.

[3]This could be why so much of technological advancement is characterized by the advancement in materials. You can only get so far by using a specific set of building blocks. At some point, you need better blocks.

[4]There is a larger article here about how it’s important to follow the things that love the most, whether this is in hobby form or if you’re lucky, work form. You will work harder at doing them better, more importantly, working harder at understanding yourself and removing your mental blocks, which will help you in all the other parts of your life.

If you’ve ever wondered[1] whether the Internet is made up of cats, think about inactivity timeouts. You watch cats playing, partway through, one of them will stop moving, distracted by something, and the other will wait for a while, then timeout and just walk away.

If you still don’t believe me, look at this picture and think about all the times your computer put itself into what felt like an infinite loop because of something you asked it to do:

There are a number of things you can see from this list. First, enlightened really likes drawing cards, it’s kind of its thing. Let’s reorder the cards to show some other patterns. I’m going to put them in ascending rune cost order, secondary sort by descending honour order, with the idea that a 3rune/1honour card is considered more powerful than a 3rune/2honour card, and you are being compensated at the end of the game with the extra honour point:

Starting with the Arha Initiate, it costs 1 rune to add ‘one free honour’ to your deck. Interestingly, Spike Vixen (+1P,+1C) and Wolf Shaman (+1R,+1C) are parallel to and similar to Heavy Infantry (+2P) and Mystic (+2R). One would expect them to be strictly more powerful, due to their relative rarity (as you can always purchase a Heavy Infantry or Mystic). Also, the next card you draw is at minimum an apprentice or militia, so you will get a minimum of +1 something with your card drawn, likely more, especially in the end game.

Temple Librarian and Arbiter of the Precipice deal with the issue of unwanted cards in your hand in slightly different ways. Each of them is overall card neutral (+2 cards, discard or banish one). It is telling that the act of banishing a card over discarding one is worth two runes in card cost, even more, as the Arbiter only gives your one honour rather than the normal two for a four-rune card in the end game. But as our previous simulations suggest, the banishing is totally worth it.

Kor the Ferromancer is a tricky card to get a bead on. At +2P,+0.5C for 3R/2H, it’s considered slightly more powerful than +1P,+1C for 2R/1H. I find this a bit surprising, as you would think the card drawing would be more important. In gameplay, it turns out that +2P is much more powerful[1] than +1P, and you end up drawing the card much more often in later gameplay, making the card worth more when it counts.

The last three cards are the most costly of the card drawing cards in the basic Ascension set. Master Dhartha (+3C for 7R/3H) is considered the most powerful card in the set[2], and it should be[3], as it gives you two extra cards, or a 40% stronger hand. Interestingly, it’s 1R/1H for +1C, 5R/2H for +2C and 7R/3H for +3C, suggesting that it’s either much easier to get 5 Runes than 7 Runes (which it is), or that +2C is that much more useful than +1C than +3C is to +2C.

Comparing Flytrap Witch (+2H/+1C) to Ascetic of the Lidless Eye (+2C), both costing 5R/2H shows how powerful card drawing is perceived to be, that drawing an additional card is worth two honour! If you have multiple card-drawing cards in your deck (as I generally do), this can easily be the case. If the card you draw is a heavy infantry, +2P can easily be worth +2H, and the cards scale up from there.

As always, thanks for reading, comment if you want specific parts of this game (or others) analyzed!

When you are giving a presentation, there are a number of decisions you have to make. How many words to put on each slide[1], what colour to make the slides[2], what you’re going to talk about[3], and many others.

Today, I want to focus on how you plan your presentation so as best to deal with ‘why did you?’ type questions. This is most helpful when you’re giving academic presentations, where you will likely have multiple people in the audience who actually know more[4] than you do about parts of what you’re talking about.

When you’re planning a presentation, it’s often tempting while you’re doing a survey of the field to go into an equal amount of depth all across the field, no matter how much you actually know about the field. This may be slightly better for the audience, but it means that in some parts of your presentation, you will not be able to answer even one ‘why?’ question[5].

It is better to decide on how many ‘why’ questions you want to be able to answer, then you can design your presentation so that there is always that amount of space between what you are presenting and your knowledge. You will be better able to serve your audience by being able to answer a reasonable depth of question, and you’re much less likely to embarrass yourself.

[1]None, if possible.
[2]Whatever helps keep the audience awake, I tend to use black on white for this reason.
[3]I recommend Keybeards and Bagpopes.
[4]Not to be confused with people who have the delightful combination of liking to hear themselves speak and the urge to tear others down while not really knowing much about the topic at hand. Sometimes this is a fine line.
[5]Cf. ‘Five Whys‘.

So, why is this? M mentioned that as humans, we have a ‘ridiculously powerful feature extraction system that is much more powerful and vastly parallel than any computer’. I’m sure some of this is because we spend years upon years training our brains to be able to recognize a dog from a blueberry muffin. But some of it is probably in the ‘design’.

What most people probably don’t know about computers is that the reason that the chips can be so fast is because of insulation between parts. It’s like how you add brakes to a car so that it can go faster. If you can insulate different parts of a chip from each other, insulate different parts of a computer from each other, using some kind of defined language to communicate between, you can spend all your time independently making each part faster and more efficient. Over (not even that much time), your computers will get (much) faster and faster. So much faster, that they start to overwhelm other designs.

This is similar to how my hard drive (10s of MB/s) is now faster than the CPU on our old 286 (10MHz)[1].

Recent generations of CPUs are designed to be multi-layered, they might have some single digit number of layers of ‘wires’ and ‘transistors'[2], and each of these layers are specifically designed to reduce cross-talk, to be as insulated as they can be from each other.

Contrast this with the brain, which while only running at about 1kHz (vs multiple GHz of CPUs), has massively interconnected neurons, with connections running in all directions, connecting to each other in all kinds of non-binary ways. More complex, not insulated at all[3], chaotic, wonderful, and delightful.

Note: The title refers to how biology is very good at making limbs which bend back and forth, while machines are good at spinning motors.

[1]Yes, I know it’s not an exact comparison, but it’s fun to do anyway.